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Record W4415300473 · doi:10.1016/j.ejps.2025.107332

Exposure-response analysis of oral and intravenous imatinib in critically ill patients with COVID-19 acute respiratory distress syndrome

2025· article· en· W4415300473 on OpenAlexaff
Medhat M. Said, Å. Braam, Erik Duijvelaar, Job R. Schippers, Leila N. Atmowihardjo, Jos W. R. Twisk, Harm Jan Bogaard, Eleonora L. Swart, Jurjan Aman, Imke H. Bartelink

Bibliographic record

VenueEuropean Journal of Pharmaceutical Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsInstitute of Infection and Immunity
FundersHorizon 2020 Framework ProgrammeInnovative Medicines InitiativeNederlandse Organisatie voor Wetenschappelijk OnderzoekZonMwNetherlands Organization for International Cooperation in Higher EducationEuropean Commission
KeywordsCritically illAcute respiratory distressImatinibClinical trialRespiratory distressMEDLINE

Abstract

fetched live from OpenAlex

• This study investigates how unbound and total imatinib and DM-imatinib, relate to clinical outcomes in critically ill COVID-19 ARDS patients. • Despite higher total imatinib exposure in ICU patients, unbound drug levels were similar to less severe cases, yet no clear link was found between imatinib exposure and clinical improvement or mortality. • Disease severity and altered protein binding affect imatinib pharmacokinetics in critical COVID-19, highlighting the importance of focusing on unbound drug concentrations to guide dosing in future trials. Imatinib, initially approved for chronic myeloid leukemia (CML) and gastrointestinal stromal tumors (GIST), was investigated in two randomized placebo-controlled trials for its potential effect on COVID-19-related ARDS (C-ARDS). A known relationship between imatinib concentrations and effectiveness exists in CML and GIST, but this is uncharacterized in critically ill C-ARDS patients, where standard dosing may not be suitable. This study aims to explore the association between unbound imatinib, total imatinib, and total N-desmethyl-imatinib exposure with clinical outcomes in critically ill C-ARDS patients. This post-hoc analysis included C-ARDS patients from the CounterCOVID and InventCOVID trials, all requiring invasive ventilation. In the CounterCOVID trial, patients received 800 mg imatinib on day 1, followed by 400 mg once daily for 9 days. In InventCOVID, the dose was 200 mg intravenously twice daily for 7 days or until ICU discharge. A pharmacokinetic (PK) model simulated the concentration-time profiles of total imatinib (T), unbound imatinib (U), and the sum of total imatinib plus its metabolite desmethyl-imatinib (PM). PK samples were used to estimate individual PK parameters, after which associations with clinical outcomes (WHO score, P/F ratio, ICU stay, ventilator-free days, and mortality) were tested using linear mixed models and regression analysis. Data from 53 patients revealed that critically ill patients reached higher total imatinib exposure but similar unbound imatinib exposure compared to others. Critical illness and concurrent treatments influenced imatinib exposure. No clear exposure-response relationship was found between imatinib exposure and clinical outcomes. Although critical illness was linked to higher imatinib exposure, no exposure-response relationship was found. Disease severity may have also impacted the drug’s effectiveness, suggesting that ICU patients may require adjusted dosing. Future clinical studies of repurposed drugs should focus on exposure-response relationships to better understand optimal dosing in new patient populations, particularly for highly protein-bound drugs. ClinicalTrials.gov Identifier: NCT04794088, registered 11 March 2021. European Clinical Trials Database (EudraCT number: 2020-005447-23).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.367
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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